help bioprobit
-------------------------------------------------------------------------------

Title

    bioprobit --   Bivariate ordered probit regression


Syntax

    Bivariate ordered probit model

        bioprobit depvar1 depvar2 varlist [if] [in] [weight] [, options]

    Simultaneous bivariate ordered probit model

        bioprobit (depvar1 [=] varlist1) (depvar2 [=] varlist2) [if] [in] [
                 weight] [, options]


Syntax for predict

        predict [type] newvar [if] [in] [, statistic outcome(outcome pair)
                nooffset]

    statistic    Description
    -------------------------------------------------------------------------
    Main
      xb1         fitted values for equation 1
      xb2         fitted values for equation 2
      stdp1       standard error of fitted values for equation 1
      stdp2       standard error of fitted values for equation 2
    -------------------------------------------------------------------------

    options               Description
    -------------------------------------------------------------------------
    Model
      offset1(varname)     offset variable for first equation
      offset2(varname)     offset variable for second equation
      collinear            keep collinear variables

    SE/Robust
      robust              synonym for vce(robust)
      cluster(varname)    adjust standard errors for intragroup correlation

    Reporting
      level(#)            set confidence level; default is level(95)

    Max option
      maximize_options    control the maximization process;
    -------------------------------------------------------------------------
    fweights, iweights, and pweights are allowed;see weight.

Description

    bioprobit fits maximum-likelihood two-equation ordered probit models of
    ordinal variables depvar1 and depvar2 on the independent variables
    indepvars1 and indepvars2.  The actual values taken on by dependent
    variables are irrelevant, except that larger values are assumed to
    correspond to "higher" outcomes.  //Up to 50 outcomes are allowed in
    Stata/SE and Intercooled Stata, and up to 20 outcomes in Small Stata//.

    See logistic estimation commands for a list of related estimation
    commands.


Options

        +-------+
    ----+ Model +------------------------------------------------------------

    offset1(varname), offset2(varname), collinear; see estimation options.

        +---------+
    ----+ Options +----------------------------------------------------------


    robust, cluster(varname); see estimation options.  cluster() can be used
        with pweights to produce estimates for unstratified cluster-sampled
        data.

        +-----------+
    ----+ Reporting +--------------------------------------------------------

    level(#); see estimation options.

        +-------------+
    ----+ Max options +------------------------------------------------------

    maximize_options: technique(algorithm_spec), iterate(#), [no]log, trace,
        hessian, gradient, showstep, tolerance(#), ltolerance(#),
        gtolerance(#), nrtolerance(#), nonrtolerance, from(init_specs); see 
        maximize.

Options for predict

    xb1 calculates the linear prediction for equation 1.

    xb2 calculates the linear prediction for equation 2.

    stdp1 calculates the standard error of the linear prediction of equation
        1.

    stdp2 calculates the standard error of the linear prediction of equation
        2.

    outcome(outcome pair) specifies for which outcome pair the predicted
        probabilities are to be calculated.  outcome() should contain pair of
        either values of the dependent variables or one of #1, #2, ..., with
        #1 meaning the first category of a dependent variable, #2 the second
        category, etc. If one of the arguments is missing then result will be
        the marginal probability, i.e. outcome(., k) wil retun Pr(y2=k)

    nooffset is relevant only if you specified offset1(varname) or
        offset2(varname) for bioprobit.  It modifies the calculations made by
        predict so that they ignore the offset variables; the linear
        predictions are treated as xb1 rather than xb1 + offset1 and xb2
        rather than as xb2 + offset2.


Examples

    . bioprobit headroom foreign price length mpg turn


Also see

    Online: biprobit, oprobit, ml